Scholar

Junkai Ji（吉君恺）

Google Scholar ID: jLfhEGcAAAAJ

Professor (Assistant), Shenzhen University

AI for Drug DesignNeural networkOptimization

Citations & Impact

All-time

Citations

1,632

H-index

i10-index

Publications

Co-authors

Contact

Resume

Academic Achievements

Research projects include Autodock Koto (a powerful molecular docking model based on evolutionary computation), Dockformer (deep learning-based molecular docking model), Hodor (molecule generation model based on deep reinforcement learning), Retrosynthetic (AI-Driven: Mapping Complex Targets to Purchasable Precursors), Drug Design Agent (FROGENT: An End-to-End Full-process Drug Design Agent), and Dendritic neural model (the fastest machine learning technique).

Research Experience

Assistant Professor at the College of Artificial Intelligence, Shenzhen University, leading the Artificial Intelligence Drug Design Research Group (ADDG).

Background

Committed to developing advanced artificial intelligence techniques to speed up drug development and reduce costs. Research topics include Drug generation, Molecular docking, Retrosynthesis, Target discovery, and Full-process drug design agent. Also interested in Neuromorphic computing and Recommendation systems.

Miscellany